KEGG

KEGG: Kyoto Encyclopedia of Genes and Genomes. KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from genomic and molecular-level information. It is a computer representation of the biological system, consisting of molecular building blocks of genes and proteins (genomic information) and chemical substances (chemical information) that are integrated with the knowledge on molecular wiring diagrams of interaction, reaction and relation networks (systems information). It also contains disease and drug information (health information) as perturbations to the biological system.


References in zbMATH (referenced in 275 articles )

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  1. Afzal, Arfan Raheen; Yang, Jing; Lu, Xuewen: Variable selection in partially linear additive hazards model with grouped covariates and a diverging number of parameters (2021)
  2. Akalin, Altuna: Computational genomics with R. With the assistance of Verdan Franke, Bora Uyar and Jonathan Ronen (2021)
  3. Akutsu, Tatsuya; Jansson, Jesper; Li, Ruiming; Takasu, Atsuhiro; Tamura, Takeyuki: New and improved algorithms for unordered tree inclusion (2021)
  4. Fernando Palluzzi, Mario Grassi: SEMgraph: An R Package for Causal Network Analysis of High-Throughput Data with Structural Equation Models (2021) arXiv
  5. He, Yinqiu; Xu, Gongjun; Wu, Chong; Pan, Wei: Asymptotically independent U-statistics in high-dimensional testing (2021)
  6. Li, Yunfan; Datta, Jyotishka; Craig, Bruce A.; Bhadra, Anindya: Joint mean-covariance estimation via the horseshoe (2021)
  7. Łukasz Szeremeta; Dominik Tomaszuk: Generating molecular entities as structured data (2021) not zbMATH
  8. Menghi, Claudio; Rizzi, Alessandro Maria; Bernasconi, Anna; Spoletini, Paola: TOrPEDO : witnessing model correctness with topological proofs (2021)
  9. Otero, Marcelo; Sarno, Silvina N.; Acebedo, Sofía L.; Ramírez, Javier A.: Tracing molecular properties throughout evolution: a chemoinformatic approach (2021)
  10. Perez-Verona, Isabel Cristina; Tribastone, Mirco; Vandin, Andrea: A large-scale assessment of exact lumping of quantitative models in the biomodels repository (2021)
  11. Pfister, Niklas; Williams, Evan G.; Peters, Jonas; Aebersold, Ruedi; Bühlmann, Peter: Stabilizing variable selection and regression (2021)
  12. Qi, Enfeng; Fu, Can; Zhai, Ying; Dong, Jianghui: Insights into protease sequence similarities by comparing substrate sequences and phylogenetic dynamics (2021)
  13. Wang, Y. X. Rachel; Li, Lexin; Li, Jingyi Jessica; Huang, Haiyan: Network modeling in biology: statistical methods for gene and brain networks (2021)
  14. Ajmal, Hamda B.; Madden, Michael G.: Inferring dynamic gene regulatory networks with low-order conditional independencies -- an evaluation of the method (2020)
  15. de Almeida, Rita M. C.; se Souza, Lars L. S.; Morais, Diego; Dalmolin, Rodrigo J. S.: Transcriptograms: a genome-wide gene expression analysis method (2020)
  16. Granata, Ilaria; Guarracino, Mario Rosario; Maddalena, Lucia; Manipur, Ichcha: Network distances for weighted digraphs (2020)
  17. Hinze, Thomas: Coping with dynamical reaction system topologies using deterministic P modules: a case study of photosynthesis (2020)
  18. Li, Chunlin; Shen, Xiaotong; Pan, Wei: Likelihood ratio tests for a large directed acyclic graph (2020)
  19. Li, Jinyu; Lai, Yutong; Zhang, Chi; Zhang, Qi: TGCnA: temporal gene coexpression network analysis using a low-rank plus sparse framework (2020)
  20. Peeters, Carel F. W.; van de Wiel, Mark A.; van Wieringen, Wessel N.: The spectral condition number plot for regularization parameter evaluation (2020)

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